Multi-spectral imaging

ABSTRACT

Systems and techniques for multi-spectral imaging. Light may be received at a multi-spectral optical module, which transmits a plurality of wavelength band portions of the received light, each having a pre-selected bandwidth between about two nanometers and about forty nanometers. The pre-selected bandwidths may be between about ten nanometers and about thirty nanometers. Each of the wavelength band portions may have the same pre-selected bandwidth, or may have different pre-selected bandwidths.

BACKGROUND

1. Field of Invention

The present disclosure relates generally to optics, and moreparticularly to systems and techniques for multi-spectral imaging.

2. Background

For some applications, existing imaging systems are not optimal. Forexample, in order to accurately determine one or more materialcharacteristics of an object (such as an object in space), existingsystems may provide for too much or too little image information.Insufficient image information may not allow accurate determination ofmaterial characteristics, while excessive information may require moreimage processing resources and processing time and thus be inefficient.

One example of a system that may be used to determine materialcharacteristics is a hyper-spectral imaging system. In a hyper-spectralimaging system, an object is imaged at a large number of narrowwavelength bands. The wavelength bands are generally less than about ananometer in width, so that detailed spectral information about theimaged object is obtained. However, data acquisition and analysis for ahyper-spectral imaging system may be complex and time consuming.

Another example of a system that may be used to determine materialcharacteristics is a television (TV) 3-color measurement system. In a TVsystem, information is obtained in three color bands; red, green, andblue. TV 3-color imaging is fast and generally inexpensive. However, theinformation obtained is limited to three broad color bands. Thus, it maybe difficult to accurately identify material properties based on imageinformation obtained using a TV 3-color imaging system.

SUMMARY

In general, in one aspect, a multi-spectral imaging system comprises animage acquisition system and a multi-spectral optical module. Themulti-spectral optical module may be configured to receive light and tosequentially transmit to the image acquisition system a plurality ofwavelength bands having a pre-selected bandwidth of between about twonanometers and about forty nanometers. In some embodiments, thepre-selected bandwidth may be between about ten nanometers and aboutthirty nanometers.

The system may further comprise a controller configured to control themulti-spectral optical module to couple each of the plurality ofwavelength bands to the image acquisition system in turn.

The multi-spectral optical module may comprise a filter configured tofilter the received light based on wavelength, and may further comprisea light formatter to format the received light to transmit substantiallyone dimensional light to the image acquisition system. The lightformatter may comprise a light blocker including an aperture. The filtermay be a linear filter, such as a linear variable filter or angularvariable filter. The multi-spectral optical module may be configured totransmit a particular one of the plurality of wavelength bands based ona relative position of a first part of the multi-spectral optical modulewith respect to a second part of the multi-spectral optical module.

In general, in another aspect, a method may comprise receiving lightfrom an object comprising one or more materials at a multi-spectraloptical module. At the multi-spectral optical module, a plurality ofwavelength band portions of the received light may be transmitted,wherein the wavelength band portions each have a pre-selected bandwidthbetween about two nanometers and about forty nanometers. Transmittingeach of the portions may comprise configuring the multi-spectral opticalmodule to transmit light included in the associated wavelength bandportion of the received light to an image acquisition system, and toexclude light outside the associated wavelength band portion. The methodmay further comprise receiving the wavelength band portions at the imageacquisition system and generating image data corresponding to each ofthe wavelength band portions. The method may further comprise processingat least some of the image data and identifying at least one material ofthe one or more materials based on the processing of at least some ofthe image data. The method may further comprise receiving light at afirst reflection angle, and subsequently receiving light at a seconddifferent reflection angle.

In general, in another aspect, an article comprising a machine-readablemedium embodying information indicative of instructions that whenperformed by one or more machines result in operations comprisingreceiving image data indicative of an optical response of a plurality ofmaterials of an object in a plurality of wavelength bands each having apre-selected bandwidth in the range from about two nm to about forty nm,wherein the image data comprises image data for a plurality of imagepixels.

The operations may further comprise comparing the image data toreference data corresponding to a plurality of candidate materials, thereference data comprising data indicative of an optical response of eachof the candidate materials for the plurality of wavelength bands. Theoperations may further comprise determining an identity of a firstmaterial of the plurality of materials corresponding to a first imagepixel of the plurality of image pixels based on the comparing, anddetermining an identity of a second material of the plurality ofmaterials corresponding to a second image pixel of the plurality ofimage pixels based on the comparing.

These and other features and advantages of the present invention will bemore readily apparent from the detailed description of the exemplaryimplementations set forth below taken in conjunction with theaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a schematic side view of an imaging system, according to someembodiments;

FIG. 1B is a front view of a linear variable filter that may be usedwith the system of FIG. 1A, according to some embodiments;

FIG. 1C is a front view of a linear angular filter that may be used withthe system of FIG. 1A, according to some embodiments;

FIG. 1D is a front view of a modifier that may be used with the systemof FIG. 1A, according to some embodiments;

FIG. 2 is a flow chart of a method that may be used with a system suchas that shown in FIG. 1A, according to some embodiments;

FIG. 3A is a greyscale representation of an image acquired at fourdifferent wavelength bands between 400 nm and 700 nm;

FIG. 3B is a corresponding graph of reflectivity versus wavelength forone pixel corresponding to a portion of the images shown in FIG. 3A;

FIG. 4 is graph of reflectivity versus wavelength for a number ofdifferent candidate materials;

FIG. 5 is a flow chart of a method that may be used to train a systemsuch as that shown in FIG. 1A; and

FIG. 6 is a flow chart of a method that may be used for setting up asystem such as the system of FIG. 1A, acquiring data, and generatingresults, according to some embodiments.

Like reference symbols in the various drawings indicate like elements.

DETAILED DESCRIPTION

As noted above, some existing imaging systems may provide too much ortoo little data to efficiently and accurately identify desired materialparameters. For example, existing systems may not be optimal fordetermining material properties of one or more objects.

Systems and techniques described herein may provide more efficientoptical imaging and analysis, for some applications. FIG. 1A shows animplementation of a system 100, according to some implementations.System 100 utilizes multi-spectral imaging techniques to efficientlydetermine a distribution of one or more material properties of an object110. For example, system 100 may be used to identify the spatialdistribution of different materials on the surface of the imaged object.

In operation, light 111 is incident at an angle θ₁ to a surface normalof an object 110 to be imaged. Light 112 from object 110 is incident ona multi-spectral optical module 115. Multi-spectral optical module 115includes components configured to modify incoming light of a broadspectrum to provide a plurality of wavelength bands to an imageacquisition system 140. Each of the wavelength bands may have a width ofabout 2 nm to about 40 nm. In some implementations, the width of thewavelength bands is about 10 nm to about 30 nm.

Module 115 accepts broadband light from a two-dimensional scene, andproduces a staggered (e.g., time-phased) plurality of output lightsamples at narrower optical bandwidth, that may be formed into completetwo-dimensional images.

In FIG. 1A, multi-spectral optical module 115 includes a filter 120 anda light modifier 130. Filter 120 may be, for example, a linear variablefilter or an angular variable (e.g. circular variable) filter. Thewavelength of the light that passes through filter 120 varies along theextent (vertical, horizontal, or angular, depending on the configurationused) of filter 120.

FIG. 1B shows a linear variable filter 120 that may be used in someembodiments. In the example of FIG. 1B, the wavelength of light that ispassed by the filter varies along the horizontal (x) direction. A bandof filter 120 of length d acts as a bandpass filter to pass light havinga wavelength band of Δλ, centered about λ₁. Some examples of linearvariable filters include filters supplied by JDSU Uniphase of San Jose,Calif., filters from Ocean Optics of Dunedin, Fla., and filters such aspart number R04610-00 from Raynard Corporation of San Clemente, Calif.

FIG. 1C a variable circular filter 120 that may be used in someembodiments. In the example of FIG. 1C, the wavelength of light that ispassed by the filter (e.g., λ₁) varies with the rotation angle Φ. A bandof filter 120 corresponding to an angular displacement ΔΦ acts as abandpass filter to pass light having a wavelength band of Δλ, centeredabout λ₁. Variable circular filters may be obtained from, for example,OCLI of Santa Rosa, Calif.

In some embodiments, different filter types may be used. For example,liquid crystal electronically tunable filters, variable etalon filters,acousto-optical filters, or other filters. However, other filter typesmay be relatively heavy or complicated, may have relatively poorefficiency, and/or may have a limited range.

Using variable filters rather than discrete filters (e.g., filters witha plurality of discrete filter elements each configured to pass aparticular bandwidth) may provide a number of benefits. For example,pseudo-continuous data may be generated, rather than discrete chunks ofdata. Additionally, the images may be spaced finer than the bandwidth.For example, for a relatively dim target, the bandwidth may be setsomewhat wider than the desired bandwidth (e.g., 10 mu), but images maybe acquired at wavelengths differing by an amount less than thebandwidth (e.g., 5 mu). A sort of “running average” is obtained, wherethe wavelength ranges for consecutive images will overlap to someextent.

Light from filter 120 is incident on a light modifier 130. Lightmodifier 130 formats received light to alter the spatial profile of thelight. Light modifier 130 may include an aperture configured to transmitonly a portion of the incident light. Light modifier 130 may bepositioned with respect to filter 120 so that the aperture transmitslight in a pre-selected narrow wavelength band and substantially blockslight outside the narrow wavelength band.

In other embodiments, light modifier may comprise optical componentsconfigured to squeeze the light received by the object (e.g., the lightcomprising the two dimensional scene) through a narrow band of thefilter corresponding to the desired wavelength band. In such anembodiment, substantially all of the received light may be available forprocessing in system 100. Exemplary systems and techniques are describedin commonly assigned U.S. patent application Ser. No. 11/138,782,entitled “Distorted Pupil Relay for Spectral Filtering,” filed on May26, 2005, which is hereby incorporated by reference.

In order to provide sufficient data to accurately identify one or morematerials of object 110 relatively quickly, the wavelength bands may beon the order of 10 nm to about 30 nm in width. In some implementations,wider or narrow bands may be used; for example between about 1 or 2nanometers in width to about 40 nanometers in width may be used. Thenumber of bands is generally between about 10 and 30, although more orfewer may be used. For example, in order to cover the visible spectrum,which spans a wavelength range of about 300 nm, about 10 to 150wavelength bands may be used.

Obtaining data for large numbers of wavelength bands may requiresignificant time and processing resources. Therefore, in someembodiments, smaller wavelength bands may be used for a portion of thespectrum (e.g., for a 50 nm wide portion of the about 300 nm widevisible spectrum). Note that the data need not be confined to thevisible spectrum. For example, image acquisition system 140 may comprisecharge coupled device (CCD) or CCD-like imagers, image intensifiertubes, or other apparatus for obtaining image data for wavelengthsoutside of the visible range (e.g., in the ultraviolet, deepultraviolet, infrared, and thermal infrared portions of theelectromagnetic spectrum).

FIG. 1D shows a front view of an exemplary embodiment of a modifier 130.Modifier 130 comprises an elongate aperture 131 in a light blocker 132.As shown in FIG. 1B, the elongate aperture 131 is a rectangular slothaving a width w. Modifier 130 may be positioned with respect to filter120 so that a particular wavelength band is transmitted through aperture131 to image acquisition system 140. Although the light at a receivingplane of optical module 115 is two dimensional, light transmitted toimage acquisition system 140 is substantially one-dimensional.

In order to acquire image data at a plurality of wavelength bands of aparticular wavelength bandwidth, the relative position of at least oneof filter 120 and modifier 130 may be changed. Referring to FIGS. 1B and1D, filter 120 may initially be positioned so that light from a firstfilter element configured to filter light having a wavelength band ofwidth Δλ centered around wavelength λ₁ is transmitted to imageacquisition system 140. Image data corresponding to λ₁ may be acquired.Filter 120, modifier 130, or both may then be moved so that a differentfilter element configured to filter light centered around a differentwavelength (such as λ₂) is aligned with aperture 131 of modifier 130,and additional image data acquired. Filter 120 and/or modifier 130 maybe moved using, for example, a stepper motor in communication with astepper motor controller or other controller.

Similarly, referring to FIGS. 1C and 1D, filter 120 may initially bepositioned so that light from a first filter element configured tofilter light having a wavelength band of width Δλ centered aroundwavelength λ₁ is transmitted to image acquisition system 140. Filter 120may then be rotated so that light from a different filter element istransmitted to image acquisition system 140. Note that the filtercharacteristics may vary continuously along the filter, so the phrase“filter element” is defined by the light coupled to the imageacquisition system, rather than by features of the filter. Note that inembodiments in which discrete filters are used, filter elements aredefined by features of the filter.

System 100 may be configured so that the width of the wavelength band isadjustable. For example, at least one of filter 120 and modifier 130 maybe adjustable so that different bandwidths may be coupled into imageacquisition system 140. This may be accomplished in a number of ways;for example, by providing an adjustable aperture, by varying therelative position of filter 120 with respect to modifier 130, and thelike. Another technique that may be used is to implement a filtercomprising a low-pass filter and a high-pass filter. Moving them withrespect to one another creates a variable bandpass filter. Variablefilter systems incorporating a low-pass filter and a high-pass filtermay be obtained from Ocean Optics of Dunedin, Fla.

Image acquisition system 140 may comprise a camera, such as a CCD(charge coupled device) camera, a CMOS (complementary metal oxidesemiconductor) camera, and/or other camera. Image acquisition system 140may comprise an image intensifier, and/or an ultraviolet, visible, orinfrared focal plane array. For each wavelength band, system 140acquires image data for a plurality of pixels corresponding to an imageof object 110. That is, each pixel includes image data for correspondingto a subdivision of the imaged portion of object 110 (and/or backgroundto object 110).

Image acquisition system 140 and/or module 115 may include one or morecomponents that are not illustrated in FIG. 1A. For example, one or morelenses, sunshades, broad-band filters, apertures, or the like may beincluded in system 100 either prior to or after module 115.

Image acquisition system 140 may be in communication with a controller150. Controller 150 may be integrated with image acquisition system 140,or may be separate. Controller 150 may be in communication with aprocessor 160 configured to process image data.

Controller 150 may control at least one of system 140, filter 120, andmodifier 130. For example, controller may output signals to filter 120that may cause filter 120 to move so that a different portion of filter120 is aligned with modifier 130. Controller 150 may further causesystem 140 to acquire data at the updated position of filter 120.

In some embodiments, controller 150 may comprise a computer device suchas a personal computer to control image acquisition system 140, as wellas one or more separate motor drive controllers (e.g., a stepper motorcontroller) for positioning filter 120 with respect to modifier 130. Insuch embodiments, processor 160 may be included in the computer device.The computer device may generate information to control motor drivecontroller(s), to control image acquisition system 140, to record imagedata, and to process image data.

Image information may be provided to processor 160. The imageinformation may comprise, for example, information indicative of a lightintensity (which is in turn indicative of reflectivity) at each of thewavelength bands for each of the image pixels.

Processor 160 may process image information to determine whetherparameters of image acquisition system 140 are adequate. For example, aspart of a set-up process, processor 160 may determine data indicative ofa gain of image acquisition system 140 so that the brightest pixel is atthe saturation limit of system 140. System 140 may be adjusted usingcontroller 150 to have the determined gain.

A system such as system 100 of FIG. 1A may provide an additionaladvantage in that module 115 and image acquisition system 140 may bemodular. That is, image acquisition system 140 may be a standardcommercial imager, and a module 115 may be used without modifying theimager.

FIG. 2 is a flow chart of a method 200 that may be used with system 100of FIGS. 1A to 1D, according to some embodiments.

At 210, light may be reflected from a portion of an object at areflection angle, and received at a system such as system 100. At 220,the received light may be filtered and modified so that a particularwavelength band having a pre-selected bandwidth is transmitted to animage acquisition system. The filtered and modified light may besubstantially one dimensional. At 230, image data may be acquired for aplurality of pixels, and processed at 240.

At 250, the system may be adjusted to acquire image data for a differentwavelength band. At 220, received light may be filtered and modified sothat the different wavelength band is transmitted to an imageacquisition system, unless the data has been acquired for all wavelengthbands of interest. Image data may again be acquired at 230, andprocessed at 240. At 260, one or more materials of the object may beidentified based on processing the image data. For example, a spatialdistribution of materials of the object may be determined based on theprocessing.

In some cases, there may be too much or too little light to adequatelydetermine at least some of the materials of the object. For example, thereceived light corresponding to one or more of the image pixels may havetoo great an intensity, and the optical system may saturate. Thus, itmay not be possible to accurately identify the material for thosepixels. Similarly, for some pixels, the received light may have toolittle intensity. The signal may not be ascertainable above the noise tothe extent necessary to determine the material for those pixels. Forcases such as those, the reflection angle may be varied, and the processmay be repeated, until sufficient data is acquired. Note that in somecircumstances, accurate identification of a material for fewer than allpixels of an image may be sufficient.

FIG. 3A shows an image at four different wavelength bands between 400 nmand 700 nm. FIG. 3B shows a corresponding graph of reflectivity versuswavelength for one pixel of the image, where the pixel is located in thecircled region of the image. Note that the images of FIG. 3A is agrey-scale representation of the response of the object to lightcorresponding to the different wavelengths. Note that each pixel in theimage may have a different spectrum associate with the particular pixel.

In order to determine the material or materials corresponding to theparticular pixel of FIG. 3B, image data may be compared to data for anumber of possible materials. FIG. 4 shows reflectivity versuswavelength for a number of different materials. The data used togenerate FIG. 4 may be used to identify an unknown material from aplurality of candidate materials.

Material identification may be performed in a number of ways. Forexample, an error may be determined by comparing the difference betweena measured reflectivity and a reference reflectivity, for eachwavelength band and for a number of candidate materials. Equation (1)below illustrates a calculation of an error E for an m-th material,where n refers to one of the N wavelength bands. R_data_(n) refers tothe measured reflectivity at the n-th wavelength band, whileR_stored_(m,n) refers to the stored reflectivity for the m-th materialat the n-th wavelength band.E _(m)=Σ_(N)(R_data_(n) −R_stored_(m,n))²  Equation (1)

In some circumstances, using higher order curve-fitting may allow formore accurate material determination. For example, a score may becalculated for an m-th material by using a weighted combination of anerror E such as that determined using Equation (1) above, and a firstorder error E′ determined using a first order error calculation such asthat illustrated by Equation (2) below. Equation (3) below showsdetermining a score Sm using both E and E′, with weighting factors a andb, respectively. $\begin{matrix}{E_{m}^{\prime} = {\sum\limits_{N}\left( \left. \frac{{\delta R\_ data}(\lambda)}{\delta\lambda} \middle| {}_{\lambda_{n}}{- \frac{\delta\quad{{Rstored}(\lambda)}}{\delta\lambda}} \right|_{\lambda_{n}} \right)^{2}}} & {{Equation}\quad(2)} \\{S_{m} = {{aE}_{m} + {bE}_{m}^{\prime}}} & {{Equation}\quad(3)}\end{matrix}$

In some embodiments, one or more correlation algorithms may be used todetermine the identity of one or more materials. Correlation algorithmsmay compare optical parameters of the material to be identified withcorresponding parameters of candidate materials. Correlation algorithmsmay determine, for example, a variance in a parameter X, S² _(X), avariance in a parameter Y, S² _(Y), a covariance of X with Y, S² _(XY),and a correlation coefficient r, as outlined in Equations (4) to (7)below. $\begin{matrix}{S_{X}^{2} = {\frac{\sum X^{2}}{N} - \frac{\left( {\sum X} \right)^{2}}{N^{2}}}} & {{Equation}\quad(4)} \\{S_{Y}^{2} = {\frac{\sum Y^{2}}{N} - \frac{\left( {\sum Y^{2}} \right)}{N^{2}}}} & {{Equation}\quad(5)} \\{S_{XY}^{2} = {\frac{\sum{XY}}{N} - \frac{\sum{X{\sum Y}}}{N^{2}}}} & {{Equation}\quad(6)} \\{r = \frac{S_{XY}^{2}}{\sqrt{\left( {S_{X}^{2} - S_{Y}^{2}} \right)}}} & {{Equation}\quad(7)}\end{matrix}$

Because the optical response of different systems under differentconditions differs, in some implementations a system may be trainedprior to being used to identify one or more materials of an object. FIG.5 shows a method 500 that may be used to train a system such as thatshown in FIG. 1A.

At 510, a sample comprising one or more known, candidate materials isprovided. At 520, the sample is imaged at a first wavelength band usinga system such as FIG. 1A, to acquire image data of a plurality of pixelscorresponding to the sample, where the identity of the material(s)corresponding to different pixel sets is known. For example, the samplemay include a copper region, an aluminum region, a Kapton™ region, andthe like. At 530, data corresponding to pixels corresponding to eachcandidate material is stored for the first wavelength band. At 540, thefilter and/or modifier is moved so that a different wavelength band isreceived in the image acquisition system, and the process is repeated.At 550, the system may be modified in other ways, and the process may berepeated for each of the wavelength bands. For example, an intensity ofa light used to illuminate the sample may be changed, a magnificationmay be changed, a reflection angle may be changed, one or moreelectronic parameters (such as a gain) may be modified, and/or othermodification may be made.

At 560, the acquired data may then be used to characterize the systemresponse to each of the candidate materials, and subsequently used toidentify the candidate materials in an acquired image to identify one ormore materials. The system may also record a response to a region knownto be “white,” in order to derive a system spectral response.Alternately, the system may be calibrated before use, or it could use analternate algorithm to derive the system spectral response, such as analgorithm using that the brightest pixel at each wavelength isequivalent to “white.”

Once a system such as system 100 of FIG. 1 is to be used to analyze thematerials of an object, a setup process may be performed prior toacquiring image data. FIG. 6 shows a process 600 for setting up asystem, acquiring data, and generating results.

At 605, a filter drive may be initialized. For example, a stepper motorcontroller may initialize a stepper motor to position the filter at abeginning position, prior to obtaining image data. At 610, an imageacquisition system such as a camera may be initialized. At 615, thefilter may be positioned at the Nth filter position (e.g., the firstposition corresponding to a first desired wavelength band). At 620, theexposure, gain, and/or other system parameters may be adjusted to firstlevel(s). The first levels may be selected to be the levels expected toyield acceptable results under the imaging conditions.

At 625, an image may be acquired using the first levels of the systemparameters. At 630, the image data may be analyzed to determine whetherthe image is within the dynamic range of the system. If it is not (e.g.,parts of the image are saturated, or the gain is insufficient to obtaina desired signal to noise ratio), one or more system parameters may beadjusted at 635, and the process repeated.

Once the system parameters are adequate, the system parameter settingsand the acquired image are stored at 640. At 645, the system determineswhether the previous filter position was the last filter position. Ifnot, the filter is adjusted to the next filter position at 650, and theprocess is repeated until data has been acquired at the last filterposition.

At 655, the images may be scaled; for example, by recorded gains. At660, the system response may be normalized. At 665, particular regionsof the image data may be selected to interrogate. At 670, the data forthe selected areas may be fit to stored data (e.g., correlated withstored spectra), and at 675 results may be output.

As noted above, systems and techniques provided herein may be used in anumber of applications. One application is the identification ofmaterials and/or material properties in space. Optical systems deployedon spacecraft generally need to be lightweight, reliable, and to operatewithout human intervention. A system such as that shown in FIG. 1A mayprovide sufficient data for material identification, without excessiveweight. Other applications include factory inspection, contaminationidentification, and other applications where the material attributes canbe distinguished by machine color that would be difficult to distinguishin a 3-color TV system.

In implementations, the above described techniques and their variationsmay be implemented as computer software instructions. Such instructionsmay be stored on one or more machine-readable storage media or devicesand are executed by, e.g., one or more computer processors, or cause themachine, to perform the described functions and operations.

A number of implementations have been described. Nevertheless, it willbe understood that various modifications may be made without departingfrom the spirit and scope of the invention. For example, additional,fewer, and/or different elements may be used to implement the invention.The order of elements in the apparatus and/or the order of actsperformed may be different than that described above (e.g., the receivedlight may be modified prior to being filtered, etc.). In anotherexample, the filter may move, or the modifier may move, or both maymove, in order to couple different wavelength bands into the imageacquisition system. Further, elements illustrated as separate may beseparate or may be integrated with other elements. Also, only thoseclaims which use the words “means for” are intended to be interpretedunder 35 USC 112, sixth paragraph. Moreover, no limitations from thespecification are intended to be read into any claims, unless thoselimitations are expressly included in the claims. Accordingly, otherimplementations are within the scope of the following claims.

1. A method comprising: receiving light from an object comprising one ormore materials at a multi-spectral optical module; at the multi-spectraloptical module, sequentially transmitting a plurality of wavelength bandportions of the received light, wherein the wavelength band portionseach have a pre-selected bandwidth between about two nanometers andabout forty nanometers, wherein transmitting each of the portionscomprises: configuring the multi-spectral optical module to transmitlight included in the associated wavelength band portion of the receivedlight and to exclude light outside the associated wavelength bandportion; and transmitting the light included in the associatedwavelength band portion of the received light to an image acquisitionsystem; receiving the wavelength band portions at the image acquisitionsystem; generating image data corresponding to each of the wavelengthband portions; processing at least some of the image data; andidentifying at least one material of the one or more materials based onthe processing at least some of the image data.
 2. The method of claim1, wherein the multi-spectral optical module comprises a filterconfigured to filter the received light based on wavelength and a lightmodifier configured to format the received light to transmit theplurality of wavelength portions of the received light.
 3. The method ofclaim 1, transmitting each of the portions further comprises modifyingthe received light to be substantially one dimensional
 4. The method ofclaim 3, wherein modifying the received light to be substantially onedimensional comprises transmitting a portion of the received lightthrough an elongate aperture.
 5. The method of claim 1, wherein themulti-spectral optical module comprises a variable linear filter.
 6. Themethod of claim 1, wherein the multi-spectral optical module comprises avariable circular filter.
 7. The method of claim 1, wherein themulti-spectral optical module comprises a filter and a light modifier,and wherein configuring the multi-spectral optical module comprisespositioning the filter with respect to the light modifier to transmitthe light included in the associated wavelength band portion of thereceived light and to exclude the light outside the associatedwavelength band portion.
 8. The method of claim 1, wherein receivinglight from an object comprising one or more materials comprisesreceiving light reflected at a first reflection angle, and furthercomprising: receiving different light at a second different reflectionangle at the multi-spectral optical module; at the multi-spectraloptical module, sequentially transmitting another plurality ofwavelength band portions of the different received light, wherein thewavelength band portions of the different received light each have apre-selected bandwidth between about two nanometers and about fortynanometers, wherein transmitting each of the portions of the differentreceived light comprises: configuring the multi-spectral optical moduleto transmit light included in the associated wavelength band portion ofthe different received light and to exclude light outside the associatedwavelength band portion of the different received light; andtransmitting the light included in the associated wavelength bandportion of the different received light to the image acquisition system;receiving the wavelength band portions of the different received lightat the image acquisition system; generating image data corresponding toeach of the wavelength band portions of the different received light;processing at least some of the image data corresponding to each of thewavelength band portions of the different received light; andidentifying at least one material of the one or more materials based onthe processing at least some of the image data corresponding to each ofthe wavelength band portions of the different received light.
 9. Themethod of claim 1, wherein processing at least some of the image datacomprises processing the at least some of the image data andcorresponding data indicative of an optical response of a plurality ofcandidate materials using a correlation algorithm.
 10. The method ofclaim 1, wherein processing at least some of the image data comprisesdetermining the score based on at least one of a first derivative and ahigher order derivative of the at least some of the image data withrespect to wavelength.
 11. The method of claim 1, wherein thepre-selected bandwidth is included in the range extending from about tennanometers to about thirty nanometers.
 12. A system, comprising: animage acquisition system; a multi-spectral optical module configured toreceive light, the module configured to sequentially transmit to theimage acquisition system a plurality of wavelength bands having apre-selected bandwidth of between about two nanometers and about fortynanometers; and a controller configured to control the multi-spectraloptical module to couple each of the plurality of wavelength bands tothe image acquisition system in turn.
 13. The system of claim 12,wherein the multi-spectral optical module comprises a filter configuredto filter the received light based on wavelength and a light formatterconfigured to format the received light to transmit substantially onedimensional light to the image acquisition system.
 14. The system ofclaim 13, wherein the filter comprises a variable filter, and a whereinthe formatter comprises a light blocker including an aperture.
 15. Thesystem of claim 14, wherein the variable filter is selected from thegroup consisting of a linear variable filter and an angular variablefilter.
 16. The system of claim 12, wherein the multi-spectral opticalmodule is configured to transmit a particular one of the plurality ofwavelength bands based on a relative position of a first part of themulti-spectral optical module with respect to a second part of themulti-spectral optical module.
 17. The system of claim 16, wherein thecontroller is configured to position at least the first part of themulti-spectral optical module with respect to the second part of themulti-spectral optical module to couple each of the plurality ofwavelength bands to the image acquisition system in turn.
 18. The systemof claim 12, wherein the pre-selected bandwidth is between about tennanometers and about thirty nanometers.
 19. An article comprising amachine-readable medium embodying information indicative of instructionsthat when performed by one or more machines result in operationscomprising: receiving image data indicative of an optical response of aplurality of materials of an object in a plurality of wavelength bandseach having a pre-selected bandwidth in the range from about two nm toabout forty nm, wherein the image data comprises image data for aplurality of image pixels; comparing the image data to reference datacorresponding to a plurality of candidate materials, the reference datacomprising data indicative of an optical response of each of thecandidate materials for the plurality of wavelength bands; determiningan identity of a first material of the plurality of materialscorresponding to a first image pixel of the plurality of image pixelsbased on the comparing; and determining an identity of a second materialof the plurality of materials corresponding to a second image pixel ofthe plurality of image pixels based on the comparing.
 20. The article ofclaim 19, wherein the comparing comprises determining an error amountusing a difference between the image data for each of the plurality ofwavelength bands and the data indicative of the optical response of atleast some of the candidate materials for the plurality of wavelengthbands.
 21. The article of claim 19, wherein the comparing comprisesdetermining a higher order error amount using a difference between aderivative with respect to wavelength of the image data for each of theplurality of wavelength bands and a derivate with respect to wavelengthof the data indicative of the optical response of at least some of thecandidate materials for the plurality of wavelength bands.
 22. Thearticle of claim 21, wherein the derivative is a first derivative. 23.The article of claim 19, wherein the pre-selected bandwidth is betweenabout ten nanometers and about thirty nanometers.